Efficient Attribute-Based Encryption with Privacy-Preserving Key Generation and Its Application in Industrial Cloud

Due to the rapid development of new technologies such as cloud computing, Internet of Things (IoT), and mobile Internet, the data volumes are exploding. Particularly, in the industrial field, a large amount of data is generated every day. How to manage and use industrial Big Data primely is a thorny challenge for every industrial enterprise manager. As an emerging form of service, cloud computing technology provides a good solution. It receives more and more attention and support due to its flexible configuration, on-demand purchase, and easy maintenance. Using cloud technology, enterprises get rid of the heavy data management work and concentrate on their main business. Although cloud technology has many advantages, there are still many problems in terms of security and privacy. To protect the confidentiality of the data, the mainstream solution is encrypting data before uploading. In order to achieve flexible access control to encrypted data, attribute-based encryption (ABE) is an outstanding candidate. At present, more and more applications are using ABE to ensure data security. However, the privacy protection issues during the key generation phase are not considered in the current ABE systems. That is to say, the key generation center (KGC) knows both of attributes and corresponding keys of each user. This problem is especially serious in the industrial big data scenario, because it will cause great damage to the business secrets of industrial enterprises. In this paper, we design a new ABE scheme that protects user\u27s privacy during key issuing. In our new scheme, we separate the functionality of attribute auditing and key generating to ensure that the KGC cannot know user\u27s attributes and that the attribute auditing center (AAC) cannot obtain the user\u27s secret key. This is ideal for many privacy-sensitive scenarios, such as industrial big data scenario

Micro-CT Imaging of RGD-Conjugated Gold Nanorods Targeting Tumor In Vivo

Gold nanomaterials as computed tomography (CT) contrast agents at lower X-ray dosage to get a higher contrast have advantages of longer imaging time and lower toxic side effects compared to current contrast agents. As a receptor for Cyclo (Arg-Gly-Asp-D-Phe-Lys) (RGD) peptide, integrin αvβ3 is overexpressed on some tumor cells and tumor neovasculature. In this paper, we conjugated the RGD peptide on the surface of gold nanorods (AuNRs), designated as RGD-AuNRs, a promising candidate in applications such as tumor targeting and imaging capability for micro-CT imaging. Integrin αvβ3-positive U87 cells and integrin αvβ3-negative HT-29 cells were chosen to establish animal models relatedly and then texted the tumor targeting ability and imaging capability of RGD-AuNRs in vitro and in vivo. The MTT assay and stability measurement showed that RGD-conjugation eliminated their cytotoxicity and improved their biocompatibility and stability. Dark-field imaging of U87 cells and HT-29 cells testified the binding affinities and uptake abilities of RGD-AuNRs, and the results showed that RGD-AuNRs were more specifical to U87 cells. The enhanced micro-CT imaging contrast of intramuscular and subcutaneous injection illustrated the feasibility of RGD-AuNRs to be contrast agents. Furthermore, the micro-CT imaging of targeting U87 and HT-29 tumor models verified the targeting abilities of RGD-AuNRs

A Delay Learning Algorithm Based on Spike Train Kernels for Spiking Neurons

Neuroscience research confirms that the synaptic delays are not constant, but can be modulated. This paper proposes a supervised delay learning algorithm for spiking neurons with temporal encoding, in which both the weight and delay of a synaptic connection can be adjusted to enhance the learning performance. The proposed algorithm firstly defines spike train kernels to transform discrete spike trains during the learning phase into continuous analog signals so that common mathematical operations can be performed on them, and then deduces the supervised learning rules of synaptic weights and delays by gradient descent method. The proposed algorithm is successfully applied to various spike train learning tasks, and the effects of parameters of synaptic delays are analyzed in detail. Experimental results show that the network with dynamic delays achieves higher learning accuracy and less learning epochs than the network with static delays. The delay learning algorithm is further validated on a practical example of an image classification problem. The results again show that it can achieve a good classification performance with a proper receptive field. Therefore, the synaptic delay learning is significant for practical applications and theoretical researches of spiking neural networks

Synoptic conditions and radar characteristics for elevated thunderstorm during a snowstorm event in Henan Province

A snowstorm event followed by the elevated thunderstorm occurred in Henan Province from February 24 to 25 in 2021. The operational forecast of all meteorological stations failed to capture the thunderstorm of this event, with the snowfall being underestimated. Using the conventional meteorological observations, the dual polarization weather radar products, and the NCEP/NCAR reanalysis with special resolution of 1° and temporal resolution of 6 h, we conducted the analysis of the synoptic conditions and the characteristics of the dual polarization radar parameters for the elevated thunderstorm during this event. Results are as follows. (1) Due to the interaction of synoptic scale systems such as the mid-latitude upper trough moving eastward and deepening, the southwest jet developing northward at 700 hPa, and the cold air diffusing southward from the surface, the convection is triggered, which resulted in the elevated thunderstorms during the snowstorm event. (2) The strongest water vapor transport is located at 700 hPa, the great value belt of water vapor flux is located in the region along the Yellow River in Henan, and there is the abundant water vapor over Henan in this event, which provide favorable thermodynamic condition for the establishment of unstable stratification in the middle level and the triggering of convection. (3) The superposition of upward branches of two secondary circulations in front of the trough provides strong upward motion for the occurrence of thunderstorms and the maintenance of snowfall. The strong vertical wind shear at 0-6 km is beneficial to the development of symmetric instability. The instability energy in the mid-and upper-level is released due to the convergence of southwest wind jet at 700 hPa and the large-scale forcing by the upper trough, thus triggering convection. (4) When the elevated thunderstorm occurs, the intensity of radar echo is greater than or equal to 45 dBz and its top height is over -20 ℃. The "bull's eye" structure and maintain of the convergence rising area are favorable for generating the thunderstorm. The main characteristics of dual polarization radar parameters during the elevated thunderstorm are that the correlation coefficient (CC) is low of 0.7-0.9, the specific differential phase (KDP) is high of 0.5°- 0.7°·km-1, and the differential reflectivity factor (ZDR) is more than 2 dB. Echo intensity over 55 dBz with large KDP of 0.5°-0.7°·km-1 corresponds to the period of frequent lightning and heavy snowfall

Improvement of Frequency Regulation in VSG-Based AC Microgrid via Adaptive Virtual Inertia

A virtual synchronous generator (VSG) control based on adaptive virtual inertia is proposed to improve dynamic frequency regulation of microgrid. When the system frequency deviates from the nominal steady-state value, the adaptive inertia control can exhibit a large inertia to slow the dynamic process and, thus, improve frequency nadir. And when the system frequency starts to return, a small inertia is shaped to accelerate system dynamics with a quick transient process. As a result, this flexible inertia property combines the merits of large inertia and small inertia, which contributes to the improvement of dynamic frequency response. The stability of the proposed algorithm is proved by Lyapunov stability theory, and the guidelines on the key control parameters are provided. Finally, both hardware-in-the-loop and experimental results demonstrate the effectiveness of the proposed control algorithm

Mantle Metasomatism and REE Enrichment in the Genetic Source of the Dalucao Carbonatite Complex (Sichuan, China): Insights from Elemental Geochemistry and In-Situ Sr Isotopes of Two Calcite Types

Carbonatites possess the highest rare earth element (REE) concentrations among all magmatic rocks, yet the mechanisms governing the enrichment of REEs in carbonatites remain enigmatic. Carbonatite-hosted calcites provide crucial mineralogical and geochemical insights into addressing this matter. In this study, we present a dataset comprising major and trace elemental geochemistry, as well as in-situ Sr isotopic data, for two types of calcites from the Dalucao carbonatite complex in Sichuan Province, China. Our primary objective is to shed light on the origin of fertile carbonatites. These calcites are believed to have originated at different stages of carbonatitic evolution. Type I calcites, characterized by a euhedral granular texture and a homogeneous surface, crystallized at the early stage of carbonatite magmatism. In contrast, type II calcites, closely associated with bastnäsite in a paragenesis, formed within a fluid setting of hydrothermal overprinting. Both calcite types exhibit highly radiogenic (87Sr/86Sr)i ratios, ranging from 0.7059 to 0.7060 for type I calcites and 0.7059 to 0.7068 for type II calcites. The high Sr concentrations (3646–7315 µg/g for type I calcites and 6566–13,427 µg/g for type II calcites) and uniform Pb isotopic compositions (206Pb/204Pb ratios of 18.23–18.27) in the Dalucao calcites refute the hypothesis of crustal assimilation as their genetic source. Instead, the radiogenic Sr isotopic compositions suggest that subducted marine sediments have contaminated the lithospheric mantle that generated the carbonatitic magma. Mineralogical evidence indicating the presence of abundant silicate minerals in the Dalucao carbonatites, combined with a compilation of published C-O isotopic data, suggests that these carbonatites may have resulted from low-degree partial melting (melting proportion <1%) of a metasomatized lithospheric mantle. Finally, we propose a comprehensive model for REE enrichment in the Dalucao carbonatite complex and explore the significance of tectonism in the genesis of fertile carbonatites